2,160 YouTube subs and yet the Spotify algo is able to know what I like and find these kids for me … needles in a haystack now algorithmically exposed: Ethan Tasch’s “Room” … all about the Magnetic Fields, I suppose.
I Ain't Sorry To Know What I Like
The Spotify algo is really picking up its game (I bought some shares). 11,900 YouTube subs, but the algo found her for me.
MALIA singing “Fussy.”
Soul Food 灵魂食品
The Spotify algo did me a solid by recommending this song … Xu has 159 subscribers, but the algo doesn’t care, it knows what I like.
The Simpsons S01 E04
“Don't correct the man, Brat.“
Unsupervised
Movies Watched -- The Furies (1950)
109 minute running time … an unexpected surprise, this was pretty wonderful … totally gobsmacked that this was made in 1950 … Anthony Mann definitely interested in Greek or Shakespearean drama … transferred to the 1870s southwest … Barbara Stanwyck rubbing Walter Huston’s sixth lumbar, Daddy dearest until things take a turn. Desert littered with hugely erect cacti, very subtle. Only problem was my Criterion Collection disc had no subtitles so I missed a lot of dialogue, and the picture was super dark, not sure if intentional. Anyway, this is a green-go for sure, see it if you haven’t. John Farr liked it too.
Don’t bite off more than you can chew
Movies Watched -- Winter Sleep (2014)
196 minute running time … yeah, 196 minutes, but this is Nuri Bilge Ceylan so he gets a pass … I watched it over two nights, like a double feature … talk talk talk, people bickering at each other in Turkish for over three hours, the joy. But I didn’t hate it, oddly. Ceylan basically makes the same movie over and over again with slight variations, and his masterpiece is Once Upon a Time in Anatolia, which is truly great (I bought the Blu-ray for repeated viewings). If you like Ceylan, you’'ll enjoy Winter Sleep.
Dick Brody wasn’t thrilled: “Ceylan paces this thin dramatic sketch as if it were a Wagner opera, with ponderous pauses and fraught gazes yearning toward depths that the movie doesn’t reach.”
Zhuo-ning Su wrote this funny line in his review: “… the one thing that most conceivably justifies the awarding of the Palme d’Or, a hypnotic pull of the film that lulls you into a meditative trance, stems most likely also from the ceaseless conversations … the desperation a viewer feels when he checks to find there are still hours on the clock is also very real.”
Great line from Manohla Dargis’s really well-written review (she gets it): “… the movie can be classed as a character study although it often plays more like one of those spiritual autopsies that directors occasionally perform on their protagonists, gutting them with degrees of gravity, glee and precision and extracting flaws like diseased organs.”
You're an unbearable man.
Movies Watched -- Billy Liar (1963)
99 minute running time … I was not in the mood for this one, it struck me as a tragedy more than a comedy, especially with his chickening out in the end … back to the row house, didn’t matter that he had his army with him … I think self-delusion can only take you so far. Depressing, but as I say, I wasn’t in the mood.
Julie Christie knew him well, put his bag back on the platform
Movies Watched -- Prevenge (2017)
98 minute running time … low-budget horror/comedy from England … it wasn’t terrible, but it also wasn’t any good. It’s a Written by, Directed by, Starring the same person deal. You can give it a miss.
Simon Abrams gets it right when he says, “The mix of tones and sensibilities in ‘Prevenge’ is meant to be aggressively absurd. But it's a fine line between goading you into relating with a mentally unstable heroine and daring viewers to check out.“
You know, they've just like got no banter, have they?
Who Pays for Robinhood Order Flow?
We can see from the Robinhood Securities - Held NMS Stocks and Options Order Routing Public Report (PDF) that there are five firms that pay for all of Robinhood’s order flow:
Notes for Chat with Traders, Episode 204
Episode 204 ... Brian Lee (70:05)
Lives in California
Pro gamer for 10 years, "FLUFFNSTUFF" (Dota 2)
Dropped out of college to become pro gamer
Traveled a lot as a pro gamer
Similar to being a rock star [but did he get laid?]
Trading another competitive "sport"
Pro gamers making multimillions now, but wasn't the case in his day (made thousands then)
Fulfilled his dream of competing at The International (2013)
Paper trading will warp you, no liquidity concerns, no emotions
A lot of trader education is scammy
Shorts microcap hard-to-borrows exclusively now, using a "mean reversion" strategy
There's an edge to taking the other side of newbie long trades
Size up your risk in a systematic way
Started with around $30,000 (his gaming winnings)
Refunded a couple times to stay over PDT (Pattern Day Trader minimum $25,000)
Changed colors of bars in ThinkOrSwim to try to control his fomo, didn't work
Built systematic entry method to defeat his fomo which has worked, no details given of course
Took him a year to become consistent, learning the rules of the game
Lost 50% of his gains when pot sector was in runaway mode
Would revenge trade tickers and would average losers
End of year two he lost all his profits, blew up his account which had grown to around $100,000
Broker bought him in at the top when he lost it all, froze when he got margin calls
Pro gamers used to taking a loss and being able to re-focus
Fiancee told him after he blew up to get a job
Without a college degree, he could only drive for Uber or work at Starbucks
Father died later that year, left some life insurance money
Mom let him re-fund account to bare minimum
Started to take things super seriously as a result
Implemented max loss rule, that's the thing that truly saved him
Equity curve is now parabolic
Wires out money regularly, treats it like a real job, hasn't sized up since reaching dream size
Doesn't want to be a superstar
Focused on small caps, screenshot 1 min and 5 min charts of all runners to find patterns
Noted patterns and figured out where to enter, stop and target to come up with at least 3 to 1 reward to risk
Connected with traders on Twitter who traded similar niche, met together on Discord after hours, collaborated
Always pick someone slighlty better than you and someone slightly worse than you to maximize learning
Loves trading trash stocks with heavy dilution, companies that need capital badly
Companies release bogus public relation announcements, create supply demand imbalance
Scales into front side of moves, then adds once supply comes in
Plays reversion to a mean, exits there (examples of "means": VWAP, moving averages, some daily level, etc.)
"Haymaker" ... running price up thousands of percent, make sure shorts get bought in
Most people who try what he does get blown out because they revenge trade, have no max loss
Best supply comes not just from dilution but also from bagholders (people stuck long the stock from higher prices)
Find companies that are toxic by nature ... same underwriters involved in all dilutions
Can identify style of play by underwriter involved, different tricks employed
Find broken charts that are full of spikes where all the gains are instantly given back
Uses calculator in Excel, inputs stop and target and generates optimal entry based on risk reward
Doesn't want to set stops too tight or too loose [Goldilocks principle]
Uses a couple different indicators to trigger him into the trade
Very patient, he maximizes moves ... average winner is six times his average loss
26% win rate on per trade basis because he cuts a lot of starters
He's confident to put on a trade every time because he understand his average win to average loss ratio
Every trade is a drop in the bucket, doesn't think about trades individually
Won't reveal his custom indicators, but does say he takes what the average trader looks at and uses that against them
Does not look at level 2 when putting on a trade, he just enters and sets stop and target
Normalize your trade outcome by betting a consistent amount
Find a goal number where you are slightly uncomfortable and use that as your R
Scale risk down when you're losing, scale risk up when you're winning
You have to feel like you deserve your gains
Once you're really comfortable with the amount you are risking, then you can move up a level to slightly uncomfortable
Will double risk on trades that he's super confident on, the A+ setup, but....
Most of his trades are the same bet size
Trades you don't take full size on, if you win, you won't feel good about it; when you lose, you're tempted to add
Beginner traders vary bet sizes wildly day to day so their results make no sense
His starter position is very small, secondary signal says take full size, tertiary signal says add to winner
Doesn't get emotional when small starter goes against him, he's instantly able to cut it
Feels he has enough experience now to be a bit more discretionary about exits (targets and stops)
If it's pushing higher midday, it's likely that he's wrong ... time of day is key
With his starter, it could be a 0.5R loss, so he can make many many attempts with 6R average win
Built his own way of understanding average true range for small caps
Figure out how much range there is, how much "meat on bone" to target, can then set stop appropriately
Waits patiently for price to get to target, or "close enough," never takes partial profits
Doesn't want "decision fatigue" of exiting and re-entering over and over
Doesn't carry positions overnight ... fees too high, 7x overnight locate fees, interest, plus gap risk too great
Hit his dream risk amount in January 2020
Increased his R by one every month this year
If your risk is too tight, you're constantly going to stop out
Don't force the range, take advantage of it ... you can't do that with a short time horizon
He doesn't have tight initial risk, he has wide initial risk, then tightens stop as price goes in his favor
Three things you must have:
1) max loss, a failsafe that will keep you from fighting something into oblivion
2) systematize your entry and exit so you can measure how you are doing
3) normalize your risk, very small R in the beginning, give yourself time to make all the mistakes you need to make
Once you are consistent, you can start to scale up; money made later will be many times your early losses [assuming you find an edge]
Twitter: @BrianLeeTrades